R Notebook

Code based on :

https://github.com/matanmazor/ignorance/blob/main/docs/hangman.Rmd

Load csv

Format Data

Make a dataframe for later use with all of the relevant information merged from the two dataframes above

Correlation

Merge

Correlation between word speed and position

A Pearson’s product-moment correlation was conducted to examine the relationship between mean position and mean speed. The analysis revealed a positive correlation between these variables, though the relationship was not statistically significant, r(7)=0.53, p=.14. The 95% confidence interval for the correlation ranged from −0.20 to 0.88, suggesting uncertainty about the true strength of the relationship.

BY SUBJ_ID

t is time. Want to look at the correlation between speed of game and predicted score given So will end up with 200 values, each one is a correlation per subject (correlation of ther 5 games)

A one-sample t-test revealed a significant positive mean correlation between speed and the measured variable, t(197)=10.32,p<.001. The 95% confidence interval for the mean correlation ranged from 0.28 to 0.41, with a sample mean of M=0.34. This suggests a robust positive relationship.

Make a dataframe for revealed and for hidden

A one-sample t-test indicated a significant positive mean correlation between speed and the measured variable in the revealed condition, t(99)=5.74,p<.001. The 95% confidence interval for the mean correlation was [0.18, 0.38], with a sample mean of M=0.28. This suggests a moderate positive relationship.

A one-sample t-test revealed a significant positive mean correlation between speed and the measured variable in the hidden condition, t(97)=9.19,p<.001. The 95% confidence interval for the mean correlation was [0.32, 0.49], with a sample mean of M=0.40. This indicates a strong positive relationship.

Combine datasets